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VASE: Object-Centric Appearance and Shape Manipulation of Real Videos

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arxiv 2401.02473 v1 pith:7I2YIZIN submitted 2024-01-04 cs.CV

VASE: Object-Centric Appearance and Shape Manipulation of Real Videos

Elia Peruzzo , Vidit Goel , Dejia Xu , Xingqian Xu , Yifan Jiang , Zhangyang Wang , Humphrey Shi , Nicu Sebe This is my paper
classification cs.CV
keywords appearancecontroldiffusioneditingframeworkmodelsmodificationsobject
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Recently, several works tackled the video editing task fostered by the success of large-scale text-to-image generative models. However, most of these methods holistically edit the frame using the text, exploiting the prior given by foundation diffusion models and focusing on improving the temporal consistency across frames. In this work, we introduce a framework that is object-centric and is designed to control both the object's appearance and, notably, to execute precise and explicit structural modifications on the object. We build our framework on a pre-trained image-conditioned diffusion model, integrate layers to handle the temporal dimension, and propose training strategies and architectural modifications to enable shape control. We evaluate our method on the image-driven video editing task showing similar performance to the state-of-the-art, and showcasing novel shape-editing capabilities. Further details, code and examples are available on our project page: https://helia95.github.io/vase-website/

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Cited by 4 Pith papers

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